Pooja Kamat

Orcid: 0000-0002-7597-0197

According to our database1, Pooja Kamat authored at least 13 papers between 2021 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2025
Artificial intelligence advances for cashew fruit maturity and quality detection: a systematic review on models, sensors, and farming applications.
J. Big Data, December, 2025

2024
Colorizing Multi-Modal Medical Data: An Autoencoder-based Approach for Enhanced Anatomical Information in X-ray Images.
EAI Endorsed Trans. Pervasive Health Technol., 2024

Towards robust automated math problem solving: a survey of statistical and deep learning approaches.
Evol. Intell., 2024

Improving the useful life of tools using active vibration control through data-driven approaches: A systematic literature review.
Eng. Appl. Artif. Intell., 2024

Explainable Predictive Maintenance of Rotating Machines Using LIME, SHAP, PDP, ICE.
IEEE Access, 2024

2023
Multi-fault diagnosis of Industrial Rotating Machines using Data-driven approach : A review of two decades of research.
Eng. Appl. Artif. Intell., 2023

Comparative Analysis of Algorithms for Cotton Plant Leaf Disease Classification from an Image.
Proceedings of the IEEE International Carnahan Conference on Security Technology, 2023

2022
Kids' Emotion Recognition Using Various Deep-Learning Models with Explainable AI.
Sensors, 2022

Enhancing Optical Character Recognition on Images with Mixed Text Using Semantic Segmentation.
J. Sens. Actuator Networks, 2022

2021
Deep learning-based anomaly-onset aware remaining useful life estimation of bearings.
PeerJ Comput. Sci., 2021

Data-driven bearing fault detection using hybrid autoencoder-LSTM deep learning approach.
Int. J. Model. Identif. Control., 2021

Explainable AI for Multimodal Credibility Analysis: Case Study of Online Beauty Health (Mis)-Information.
IEEE Access, 2021

Data-Driven Remaining Useful Life Estimation for Milling Process: Sensors, Algorithms, Datasets, and Future Directions.
IEEE Access, 2021


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